Chapter 5 Physical Database Design Modern Database Management

Objectives n n n n Define terms Describe the physical database design process Choose storage formats for attributes Select appropriate file organizations Describe three types of file organization Describe indexes and their appropriate use Translate a database model into efficient structures Know when and how to use denormalization Chapter 5 © 2011 Pearson Education 2

Physical Database Design n n Purpose–translate the logical description of data into the technical specifications for storing and retrieving data Goal–create a design for storing data that will provide adequate performance and insure database integrity, security, and recoverability Chapter 5 © 2011 Pearson Education 3

Physical Design Process Inputs l. Normalized l. Volume relations definitions l. Response time expectations security needs l. Backup/recovery l. Integrity l. DBMS l. Attribute estimates l. Attribute l. Data Decisions needs l. Physical record descriptions (doesn’t always match logical design) Leads to l. File organizations l. Indexes and database architectures expectations technology used Chapter 5 data types l. Query © 2011 Pearson Education optimization 4

Figure 5 -1 Composite usage map (Pine Valley Furniture Company) Chapter 5 © 2011

Figure 5 -1 Composite usage map (Pine Valley Furniture Company) (cont. ) Data volumes

Figure 5 -1 Composite usage map (Pine Valley Furniture Company) (cont. ) Access Frequencies

Figure 5 -1 Composite usage map (Pine Valley Furniture Company) (cont. ) Usage analysis: 14, 000 purchased parts accessed per hour 8000 quotations accessed from these 140 purchased part accesses 7000 suppliers accessed from these 8000 quotation accesses Chapter 5 © 2011 Pearson Education 8

Figure 5 -1 Composite usage map (Pine Valley Furniture Company) (cont. ) Usage analysis: 7500 suppliers accessed per hour 4000 quotations accessed from these 7500 supplier accesses 4000 purchased parts accessed from these 4000 quotation accesses Chapter 5 © 2011 Pearson Education 9

Designing Fields n Field: smallest unit of data in database n Field design n

Choosing Data Types n n n n CHAR–fixed-length character VARCHAR 2–variable-length character (memo) LONG–large number NUMBER–positive/negative number INEGER–positive/negative whole number DATE–actual date BLOB–binary large object (good for graphics, sound clips, etc. ) Chapter 5 © 2011 Pearson Education 11

Figure 5 -2 Example of a code look-up table (Pine Valley Furniture Company) Code

Field Data Integrity n n Default value–assumed value if no explicit value Range control–allowable value limitations (constraints or validation rules) Null value control–allowing or prohibiting empty fields Referential integrity–range control (and null value allowances) foreign-key to primarykey match-ups Sarbanes-Oxley Act (SOX) legislates importance of financial data integrity • 存入資料庫的是合法資料 • 完整欄位層級的稽核軌跡 Chapter 5 © 2011 Pearson Education 13

Handling Missing Data n n n Substitute an estimate of the missing value (e. g. , using a formula) Construct a report listing missing values In programs, ignore missing data unless the value is significant (sensitivity testing) Triggers can be used to perform these operations • 當有null 時記錄缺值項目至檔案 • 定期產生缺值檔案報表 Chapter 5 © 2011 Pearson Education 14

Physical Records n n n Physical Record: A group of fields stored in adjacent memory locations and retrieved together as a unit Page: The amount of data read or written in one I/O operation Blocking Factor: The number of physical records per page Chapter 5 © 2011 Pearson Education 15

Data Structure for Data Table Chapter 5 © 2011 Pearson Education 19

Denormalization n n Transforming normalized relations into nonnormalized physical record specifications Benefits: n n Costs (due to data duplication) n n n Can improve performance (speed) by reducing number of table lookups (i. e. reduce number of necessary join queries) Wasted storage space Data integrity/consistency threats Common denormalization opportunities n n n One-to-one relationship (Fig. 5 -3) Many-to-many relationship with non-key attributes (associative entity) (Fig. 5 -4) Reference data (1: N relationship where 1 -side has data not used in any other relationship) (Fig. 5 -5) Chapter 5 © 2011 Pearson Education 20

Figure 5 -3 A possible denormalization situation: two entities with oneto-one relationship Chapter 5

Figure 5 -4 A possible denormalization situation: a many-to-many relationship with nonkey attributes Extra

Figure 5 -5 A possible denormalization situation: reference data Extra table access required Data

Partitioning n Horizontal Partitioning: Distributing the rows of a table into several separate files n n n Vertical Partitioning: Distributing the columns of a table into several separate relations n n n Useful for situations where different users need access to different rows Three types: Key Range Partitioning, Hash Partitioning, or Composite Partitioning Useful for situations where different users need access to different columns The primary key must be repeated in each file Combinations of Horizontal and Vertical Partitions often correspond with User Schemas (user views) Chapter 5 © 2011 Pearson Education 24

Partitioning (cont. ) n Advantages of Partitioning: n n n Efficiency: Records used together are grouped together Local optimization: Each partition can be optimized for performance Security: data not relevant to users are segregated Recovery and uptime: smaller files take less time to back up Load balancing: Partitions stored on different disks, reduces contention Disadvantages of Partitioning: n n n Inconsistent access speed: Slow retrievals across partitions Complexity: Non-transparent partitioning (非透通性的分割, 需較複雜的程式) Extra space or update time: Duplicate data; access from multiple partitions Chapter 5 © 2011 Pearson Education 25

Oracle 11 g Horizontal Partitioning Methods n Range partitioning n n Hash partitioning n n Partitions defined via hash functions Will guarantee balanced distribution of rows Partition could contain widely varying valued fields List partitioning n n Partitions defined by range of field values Could result in unbalanced distribution of rows Like-valued fields share partitions Based on predefined lists of values for the partitioning key Composite partitioning n Combination of the other approaches Chapter 5 © 2011 Pearson Education 26

Designing Physical Files n Physical File: n n A named portion of secondary memory allocated for the purpose of storing physical records Tablespace–named set of disk storage elements in which physical files for database tables can be stored Extent–contiguous section of disk space (一段連續 ( 的磁碟儲存空間 ) Constructs to link two pieces of data: n n Sequential storage Pointers–field of data that can be used to locate related fields or records Chapter 5 © 2011 Pearson Education 27

Figure 5 -6 DBMS terminology in an Oracle 11 g environment Chapter 5 ©

Oracle Data Storage Logical Structure Rows Data Block Data Block Data Block Data Block

File Organizations n n Technique for physically arranging records of a file on secondary storage Factors for selecting file organization: n n n n Fast data retrieval and throughput Efficient storage space utilization Protection from failure and data loss Minimizing need for reorganization Accommodating growth Security from unauthorized use Types of file organizations n n n Sequential Indexed Hashed Chapter 5 © 2011 Pearson Education 30

Figure 5 -7 a Sequential file organization Records of the file are stored in sequence by the primary key field values 1 2 If sorted – every insert or delete requires resort If not sorted Average time to find desired record = n/2 Chapter 5 n © 2011 Pearson Education 31

Indexed File Organizations n n Indexed File Organization: the storage of records either sequentially or nonsequentially with an index that allows software to locate individual records Index(索引 ): a table or other data structure Index( used to determine in a file the location of records that satisfy some condition Primary keys are automatically indexed Other fields or combinations of fields can also be indexed; these are called secondary keys (or nonunique keys) Chapter 5 © 2011 Pearson Education 32

Figure 5 -7 b Indexed file organization uses a tree search Average time to

Figure 5 -7 c Hashed file organization Hash algorithm Usually uses divisionremainder to determine record position. Records with same position are grouped in lists. Chapter 5 © 2011 Pearson Education 34

Figure 6 -8 Join Indexes–speeds up join operations b) Join index for matching foreign

Clustering Files n n In some relational DBMSs, related records from different tables can be stored together in the same disk area Useful for improving performance of join operations Primary key records of the main table are stored adjacent to associated foreign key records of the dependent table e. g. Oracle has a CREATE CLUSTER command Chapter 5 © 2011 Pearson Education 37

Rules for Using Indexes 1. Use on larger tables 2. Index the primary key of each table 3. Index search fields (fields frequently in WHERE clause) 4. Fields in SQL ORDER BY and GROUP BY commands 5. When there are >100 values but not when there are <30 values Chapter 5 © 2011 Pearson Education 38

Rules for Using Indexes (cont. ) 6. Avoid use of indexes for fields with long values; perhaps compress values first 7. If key to index is used to determine location of record, use surrogate (like sequence nbr) to allow even spread in storage area 8. DBMS may have limit on number of indexes per table and number of bytes per indexed field(s) 9. Be careful of indexing attributes with null values; many DBMSs will not recognize null values in an index search Chapter 5 © 2011 Pearson Education 39

Query Optimization n Parallel query processing–possible when working in multiprocessor systems Overriding automatic query optimization–allows for query writers to preempt the automated optimization Picking data block size–factors to consider include: n n Block contention, random and sequential row access speed, row size Balancing I/O across disk controllers Chapter 5 © 2011 Pearson Education 40

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Copyright © 2011 Pearson Education Chapter 5 © 2011 Pearson Education 41